【摘要】 研究单转运系统分布式置换流水线调度问题，任一工厂内连续两台机器间有一台运输能力有限的转运机器人。基于此，提出一种多策略融合改进遗传算法以最小化最大完工时间。引入Logistic-tent混沌搜索、基于K-均值聚类的NEH算法和修正NEH算法以改善初始工厂加工序列群的质量，运用结合均匀多点交叉和互换变异的自适应交叉变异算子或工厂内/间交叉变异算子进行解的调整，设计一种基于主工厂的邻域搜索(key-factory-based local search, KFLS)和半初始化策略进行再次优化。仿真结果表明了该算法的有效性。更多还原

【Abstract】 A distributed permutation flowline problem of single-transporter systems was studied where an available transport robot with limited transport capacity between two continuous machines exist in any factory. Based on this, the multi-strategy fusion improved genetic algorithm was proposed to minimize the maximum completion time. The Logistic-tent chaotic search, Nawaz-Enscore-Ham(NEH) algorithm based on K-means clustering and the modified NEH algorithm were introduced to improve the quality of the initial factory processing sequence group. The self-adaptive crossover and mutation operators based on uniform multi-point crossover and exchange mutation or inter/external-factory crossover and mutation operators were applied to adjust solutions. The key-factory-based local search and semi-initialization strategy were designed for re-optimization. Simulation results show that the algorithm is effective.更多还原